ABSTRACT
Objective: As traditional techniques for microscopic identification of Chinese medicines currently lack objective and high-quality reference images, here we developed a systemic procedure to be used in microscopic identification of Chinese medicines, which would lead to more objective, effective and accurate identification process. Methods: Spatholobi Caulis (Jixueteng in Chinese) was used as the specimen in the development of such procedure. Jixueteng samples were microscopically examined in bright- and dark-field microscopy. Microscopic images were obtained by regular, EDF, and image stitching techniques. Results: The microscopic images of the characteristics in pulverized Jixueteng were captured, thanks to EDF imaging and image stitching techniques which allowed the detailed and full sighting of each characteristic to be obtained simultaneously. Different layers in anatomical transverse section, including cork, phelloderm, cortex, phloem, cambium, xylem and pith, were distinctively observed. Moreover, by comparing images of bright- and dark-field microscopy, birefringent and non- birefringent components could readily be distinguished. Conclusion: With application of the developed procedure, high-definition, panoramic and microscopic images were acquired, which could be used as the reference images for microscopic identification of Chinese medicines.
ABSTRACT
OBJECTIVE:To extract the feature of Achyranthes bidentata and Cyathula officinalis,and to establish image recog-nition method. METHODS:The microscopic image stitching of A. bidentata and C. officinalis was implemented by MATLAB. The color,invariant moment,stripes and the features of vascular bundle in cross section were extracted. The data was organized into da-ta matrix,and then data matrix was standardized by Zscore function;principal components were analyzed through Princomp func-tion. BP nerve network recognition mode was adopted. RESULTS:The microstructures in the micro images of the samples were kept integrated. The measured data of 27 characteristics were acquired in each group of sample. Through principal component analy-sis,the parameters of 11 main components were selected to establish BP never network. The average recognition rate of BP nerve network was 100% between 2 medicinal material relatives (n=50). CONCLUSIONS:The method can be used for micro-image auto Stitching of Chinese medicinal materials and image recognition of A. bidentata and C. officinalis.
ABSTRACT
OBJETIVO: Propor um método reprodutível, de fácil utilização e de baixo custo para a digitalização de filmes radiográficos de todos os tamanhos padrões, concentrando nossos esforços em filmes radiográficos de tórax. MATERIAIS E MÉTODOS: O objetivo de baixo custo ditou o uso de um escâner A4 com adaptador de transparência, bem como um software de costura de imagens otimizado, que tira proveito da geometria do escâner e área de captura constante, bem como o conhecimento das dimensões dos filmes radiográficos padrões. RESULTADOS: O resultado final do método proposto é uma imagem de alta resolução com bom contraste e sem artefatos de costura perceptíveis. CONCLUSÃO: O método de digitalização proposto usando um escâner A4 possibilita reprodutibilidade, excelente qualidade de imagem e alto grau de certeza na identificação de lesões.
OBJECTIVE: To propose a reproducible, user friendly and low cost method for digitization of radiographic films of all the standard sizes, focusing efforts on chest X-ray films. MATERIALS AND METHODS: The focus on low cost have dictated the use of an A4 scanner with transparency adapter, as well as an optimized image stitching software that takes advantage of the scanner geometry and constant capture area, besides the knowledge of the standard X-ray film sizes. RESULTS: The end result of the proposed method is a high resolution image with good contrast and no perceptible stitching artifacts. CONCLUSION: The proposed digitization method with an A4 scanner allows reproducibility, excellent image quality and high degree of certainty in the identification of lesions.